Age-specific differences of dual<i>n</i>-back training

Salminen, Tiina; Frensch, Peter A.; Strobach, Tilo; Schubert, Torsten

doi:10.1080/13825585.2015.1031723

Cited by 39 publications

(25 citation statements)

References 62 publications

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“…Their results demonstrated transfer from WM training to all aspects of executive function except coordination of concurrent performance, which the authors attributed to a “lack of commonalities” between the trained and target tasks (e.g., differences in the extent to which speeded processing was necessary for optimal performance). Salminen et al’s (2012) results reinforce the notion that transfer effects depend on specific cognitive processes shared by the WM training and target tasks (see also Persson et al, 2007 ; Karbach and Kray, 2009 ; Sprenger et al, 2013 ; Salminen et al, 2015 ).…”

Section: Introductionsupporting

confidence: 76%

Transfer of training from one working memory task to another: behavioural and neural evidence

Beatty

Jobidon

Bouak

et al. 2015

Front. Syst. Neurosci.

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N-back working memory (WM) tasks necessitate the maintenance and updating of dynamic rehearsal sets during performance. The delayed matching-to-sample (dMTS) task is another WM task, which in turn involves the encoding, maintenance, and retrieval of stimulus representations in sequential order. Because both n-back and dMTS engage WM function, we hypothesized that compared to a control task not taxing WM, training on the n-back task would be associated with better performance on dMTS by virtue of training a shared mental capacity. We tested this hypothesis by randomly assigning subjects (N = 43) to train on either the n-back (including 2-back and 3-back levels) or an active control task. Following training, dMTS was administered in the fMRI scanner. The n-back group performed marginally better than the active control group on dMTS. In addition, although the n-back group improved more on the less difficult 2-back level than the more difficult 3-back level across training sessions, it was improvement on the 3-back level that accounted for 21% of the variance in dMTS performance. For the control group, improvement in training across sessions was unrelated to dMTS performance. At the neural level, greater activation in the left inferior frontal gyrus, right posterior parietal cortex, and the cerebellum distinguished the n-back group from the control group in the maintenance phase of dMTS. Degree of improvement on the 3-back level across training sessions was correlated with activation in right lateral prefrontal and motor cortices in the maintenance phase of dMTS. Our results suggest that although n-back training is more likely to improve performance in easier blocks, it is improvement in more difficult blocks that is predictive of performance on a target task drawing on WM. In addition, the extent to which training on a task can transfer to another task is likely due to the engagement of shared cognitive capacities and underlying neural substrates—in this case WM.

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Section: Introductionsupporting

confidence: 76%

Transfer of training from one working memory task to another: behavioural and neural evidence

Beatty

Jobidon

Bouak

et al. 2015

Front. Syst. Neurosci.

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“…This could be interpreted as evidence that this type of training improved switching abilities and thus cognitive flexibility (Klingberg 2010). This later finding is inconsistent with other studies; these other studies showed no transfer from working memory updating training to the ability to switch between tasks (e.g., Salminen et al 2016a). However, it should also be noted that the switching demands in the TMT 2 (related to processing alternations between letters and digits) are much less pronounced (and of a somewhat different kind) than in other task switching paradigms (e.g., see Kiesel et al 2010, for a review), which makes it difficult to directly compare training effects across studies.…”

Section: Discussion Of the Present Findings And Relations To Other Trcontrasting

confidence: 56%

Evaluating the Effectiveness of Commercial Brain Game Training with Working-Memory Tasks

Strobach

Huestegge

2017

J Cogn Enhanc

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Commercial brain games are home-and computerbased cognitive trainings that are industrially offered and promise to enhance cognitive functioning by repeating cognitive tasks. Despite compelling evidence for the effectiveness of cognitive trainings in various domains and populations, the assumption of brain games' effects on people's minds has been challenged. However, there are only very few attempts to systematically evaluate the effectiveness of such games under ecologically valid training conditions. To approach this gap in the literature, we applied commercially available training tasks assumed to tap into working memory updating and capacity. The effectiveness of this training was measured by utilizing pre-and post-tests in trained tasks (criterion tasks), untrained transfer tasks from the assumed training domains (near-transfer tasks), as well as from the domains processing speed, shifting, inhibition, reasoning, and self-reported cognitive failures (far-transfer tasks). Training as well as pre-posttests were completely administered home-based. In contrast to an active control group, a training group improved performance in the criterion tasks and near-transfer tasks. Improved performance was also evident in processing speed and shifting tasks (i.e., far-transfer tasks), but these improvements were not as conclusive as those in near-transfer tasks. Further, the number of reported cognitive failures was reduced in the training in contrast to the control group at post-test. Performance improvements were more pronounced for highperforming participants (i.e., magnification effects). In general, this study provides an evaluation of the effectiveness of a particular set of working-memory training tasks in an ecologically valid setting in the context of brain games.

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“…The aim of the present study is to verify whether N ‐back task performance improves during N ‐back training and EEG recording, and whether transfer effects to other (untrained) cognitive functions can be observed, such as spatial memory, attention, and fluid intelligence, in two different groups of healthy young and older subjects. Although mixed results have been reported (Clark, Lawlor‐Savage, & Goghari, ; Lawlor‐Savage & Goghari, ; Salminen, Frensch, Strobach, & Schubert, ; Stephenson, & Halpern, ), in light of the results obtained in previous studies for both near‐ (Li et al, ; Stephenson & Halpern, ) and far‐transfer effects (Jaeggi et al, ) in healthy young adults and near‐ (Heinzel et al, ; Stepankova et al, ) and far‐transfer effects (Borella et al, ; Heinzel et al, ) in healthy older adults, we hypothesize that improvements in the trained task and near‐ and far‐transfer effects are observed in both age‐groups, with greater gains in young compared to older adults. Besides behavioral responses, we will also record ERP responses as they have shown to reflect the time course of cognitive and sensory processes during cognitive task performance.…”

Section: Introductionmentioning

confidence: 96%

N‐back training and transfer effects revealed by behavioral responses and EEG

et al. 2018

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IntroductionCognitive function performance decreases in older individuals compared to young adults. To curb this decline, cognitive training is applied, but it is not clear whether it improves only the trained task or also other cognitive functions. To investigate this, we considered an N‐back working memory (WM) training task and verified whether it improves both trained WM and untrained cognitive functions.MethodsAs EEG studies have noted task difficulty and age‐related changes in time‐locked EEG responses, called event‐related potentials (ERPs), we focused on the relation between the P300 ERP component, task difficulty level, and behavior response accuracy and reaction time (RT) in young and older healthy adults. We used two groups of young and older healthy participants to assess the effect of N‐back training: cognitive training group (CTG) and passive control group (PCG). Before and after training, cognitive tests were administered to both groups to evaluate transfer effects.ResultsDespite the observed age‐related differences in the P300 ERP component and in terms of RT and accuracy, our findings demonstrate a stronger improvement in the trained task for older CTGs compared to younger CTGs, larger near‐ and far‐transfer effect to WM and fluid intelligence for both younger and older CTGs, and a far‐transfer effect to attention but only for older adults. Significant differences in response accuracy were shown between young and older subjects in spatial memory and attention tests.ConclusionThe application of a WM training is a promising tool for both healthy adults, and in particular for older subjects, as it showed physiological and behavioral differences in cognitive plasticity across life span and evidence of benefits in the trained task and near‐/far‐transfer effects to other cognitive functions.

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Age-specific differences of dualn-back training

Cited by 39 publications

References 62 publications

Transfer of training from one working memory task to another: behavioural and neural evidence

Transfer of training from one working memory task to another: behavioural and neural evidence

Evaluating the Effectiveness of Commercial Brain Game Training with Working-Memory Tasks

N‐back training and transfer effects revealed by behavioral responses and EEG

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